Zbigniew W. Raś – författare
Foundations of Intelligent Systems
24th International Symposium, ISMIS 2018, Limassol, Cyprus, October 29–31, 2018, Proceedings
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This book constitutes the proceedings of the 24th International Symposium on Foundations of Intelligent Systems, ISMIS 2018, held in Limassol, Cyprus, in October 2018.
The 32 full, 8 short, and 4 application papers presented in this volume were carefully reviewed and selected from 59 submissions. The papers deal with topics such as bioinformatics and health informatics, graph mining, image analysis, intelligent systems, mining complex patterns, novelty detection and class imbalance, social data analysis, spatio-temporal analysis, and topic modeling and opinion mining. In addition, three special sessions were organized, namely: Special Session on Granular and Soft Clustering for Data Science, Special Session on Intelligent Methodologies for Traffic Data Analysis and Mining, and Special Session on Advanced Methods in Machine Learning for Modeling Complex Data.
Recommender System for Improving Customer Loyalty
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This book presents the Recommender System for Improving Customer Loyalty. New and innovative products have begun appearing from a wide variety of countries, which has increased the need to improve the customer experience. When a customer spends hundreds of thousands of dollars on a piece of equipment, keeping it running efficiently is critical to achieving the desired return on investment. Moreover, managers have discovered that delivering a better customer experience pays off in a number of ways. A study of publicly traded companies conducted by Watermark Consulting found that from 2007 to 2013, companies with a better customer service generated a total return to shareholders that was 26 points higher than the S&P 500. This is only one of many studies that illustrate the measurable value of providing a better service experience.
The Recommender System presented here addresses several important issues. (1) It provides a decision framework to help managers determine which actions are likely to have the greatest impact on the Net Promoter Score. (2) The results are based on multiple clients. The data mining techniques employed in the Recommender System allow users to “learn” from the experiences of others, without sharing proprietary information. This dramatically enhances the power of the system. (3) It supplements traditional text mining options. Text mining can be used to identify the frequency with which topics are mentioned, and the sentiment associated with a given topic. The Recommender System allows users to view specific, anonymous comments associated with actual customers. Studying these comments can provide highly accurate insights into the steps that can be taken to improve the customer experience. (4) Lastly, the system provides a sensitivity analysis feature. In some cases, certain actions can be more easily implemented than others. The Recommender System allows managers to “weigh” these actions and determine which ones would have a greater impact.Recommender System for Improving Customer Loyalty
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Foundations of Intelligent Systems
25th International Symposium, ISMIS 2020, Graz, Austria, September 23–25, 2020, Proceedings
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This book constitutes the proceedings of the 25th International Symposium on Foundations of Intelligent Systems, ISMIS 2020, held in Graz, Austria, in October 2020. The conference was held virtually due to the COVID-19 pandemic.
The 35 full and 8 short papers presented in this volume were carefully reviewed and selected from 79 submissions. Included is also one invited talk. The papers deal with topics such as natural language processing; deep learning and embeddings; digital signal processing; modelling and reasoning; and machine learning applications.
ECML PKDD 2020 Workshops
Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14–18, 2020, Proceedings
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Music recommendation systems are becoming more and more popular. The increasing amount of personal data left by users on social media contributes to more accurate inference of the user’s musical preferences and the same to quality of personalized systems. Health recommendation systems have become indispensable tools in decision making processes in the healthcare sector. Their main objective is to ensure the availability of valuable information at the right time by ensuring information quality, trustworthiness, authentication, and privacy concerns. Medical doctors deal with various kinds of diseases in which the music therapy helps to improve symptoms. Listening to music may improve heart rate, respiratory rate, and blood pressure in people with heart disease. Sound healing therapy uses aspects of music to improve physical and emotional health and well-being. The book presents a variety of approaches useful to create recommendation systems in healthcare, music, and in music therapy.
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This book presents a selection of papers from the industrial track of ISMIS 2020. The selection emphasizes broad applicability of artificial intelligence (AI) technologies in various industrial fields. The aim of the book is to fertilize preliminary ideas of readers on the application of AI by means of already successfully implemented application examples. Furthermore, the development of new ideas and concepts shall be motivated by the variety of different application examples. The spectrum of the presented contributions ranges from education and training, industrial applications in production and logistics to the development of new approaches in basic research, which will further expand the possibilities of future applications of AI in industrial settings. This broad spectrum gives readers working in the industrial as well as the academic field a good overview of the state of the art in the field of methodologies for intelligent systems.
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Foundations of Intelligent Systems
26th International Symposium, ISMIS 2022, Cosenza, Italy, October 3–5, 2022, Proceedings
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Foundations of Intelligent Systems
21st International Symposium, ISMIS 2014, Roskilde, Denmark, June 25-27, 2014. Proceedings
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New Frontiers in Mining Complex Patterns
Second International Workshop, NFMCP 2013, Held in Conjunction with ECML-PKDD 2013, Prague, Czech Republic, September 27, 2013, Revised Selected Papers
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New Frontiers in Mining Complex Patterns
Third International Workshop, NFMCP 2014, Held in Conjunction with ECML-PKDD 2014, Nancy, France, September 19, 2014, Revised Selected Papers
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Foundations of Intelligent Systems
22nd International Symposium, ISMIS 2015, Lyon, France, October 21-23, 2015, Proceedings
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This book constitutes the refereed proceedings of the 22ndInternational Symposium on Methodologies for Intelligent Systems, ISMIS 2015,held in Lyon, France, in October 2015.
The 31 revised full papers presented together with 18short papers were carefully reviewed and selected from 67 submissions. Thepapers are organized in topical sections on data mining methods; databases,information retrieval, recommender systems; machine learning; knowledgerepresentation, semantic web; emotion recognition, music information retrieval;network analysis, multi-agent systems; applications; planning, classification;and textual data analysis and mining.
New Frontiers in Mining Complex Patterns
4th International Workshop, NFMCP 2015, Held in Conjunction with ECML-PKDD 2015, Porto, Portugal, September 7, 2015, Revised Selected Papers
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This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2015, held in conjunction with ECML-PKDD 2015 in Porto, Portugal, in September 2015.
The 15 revised full papers presented together with one invited talk were carefully reviewed and selected from 19 submissions. Theyillustrate advanced data mining techniques which preserve the informative richness of complex data and allow for efficient and effective identification of complex information units present in such data. The papers are organized in the following sections: data stream mining, classification, mining complex data, and sequences.
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